Abstract
Causal graphs provide a key tool for optimizing the validity of causal effect estimates. Although a large literature exists on the mathematical theory underlying the use of causal graphs, less literature exists to aid applied researchers in understanding how best to develop and use causal graphs in their research projects. We sought to understand why researchers do or do not regularly use DAGs by surveying practicing epidemiologists and medical researchers on their knowledge, level of interest, attitudes, and practices towards the use of causal graphs in applied epidemiology and health research. We used Twitter and the Society for Epidemiologic Research to disseminate the survey. Overall, a majority of participants reported being comfortable with using causal graphs and reported using them ‘sometimes’, ‘often’, or ‘always’ in their research. Having received training appeared to improve comprehension of the assumptions displayed in causal graphs. Many of the respondents who did not use causal graphs reported lack of knowledge as a barrier to using DAGs in their research. Causal graphs are of interest to epidemiologists and medical researchers, but there are several barriers to their uptake. Additional training and clearer guidance are needed. In addition, methodological developments regarding visualization of effect measure modification and interaction on causal graphs is needed.
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The full survey used to obtain these results is included in the supplementary material.
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Acknowledgements
The authors would like to thank the survey participants, the Society for Epidemiologic Research, and everyone on #epitwitter who helped spread the word about our survey.
Funding
EJM and RBM were partly funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) R21HD098733. JPD was supported by grant K12-HL138039 from the National Heart, Lung, and Blood Institute (National Institutes of Health, Bethesda, MD, USA). ECC was supported by grant K01HD100222 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD).
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In terms of author contributions for this paper; RBM and EJM conceived of the idea; RBM, EJM and EC designed the survey; and all authors approved the survey instrument and contributed to the manuscript writing.
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The survey was exempted by the Boston University School of Public Health Institutional Review Board. The surveys were completely anonymous and no IP addresses were collected.
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Barnard-Mayers, R., Childs, E., Corlin, L. et al. Assessing knowledge, attitudes, and practices towards causal directed acyclic graphs: a qualitative research project. Eur J Epidemiol 36, 659–667 (2021). https://doi.org/10.1007/s10654-021-00771-3
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DOI: https://doi.org/10.1007/s10654-021-00771-3